Lead ML Modeling Engineer (Lead Data Scientist) | Flextime & Fully Remote Work /JLPT N1 Level

With the objective of reducing the operational workload of company-wide AI utilization, you will be responsible for development tasks centered on data pipelines, APIs, and application integration. Depending on your experience, you will also be tasked with high-priority business areas currently being driven by the team, such as incorporating algorithms into major products., (Role of AI Application Engineer (ML Engineer))

Development of AI Agents & Promotion of Company-wide AI Implementation

・Development work aimed at reducing operational workload associated with company-wide AI utilization

・Development of internal operational efficiency tools leveraging Generative AI APIs and Slack Bots

・Visualization via BI dashboards

・Updates to data quality management

・etc.

Sophistication of Matching Algorithms for Existing Products

・Development, improvement, and operation of the following within with/Omiai:

・Mutual recommendation models

・Recommendation engines

・etc.

*Recruitment Background

The company group is seeking an ML Engineer against the background of business expansion into new domains, the sophistication of matching algorithms in its existing mainstay dating and marriage matching application business, and an increasing need to reduce the company-wide operational workload through AI utilization.

*Team Structure

You will join the Data Strategy Office, undertaking the company-wide AI implementation mission while working in close alignment with both the dating and marriage matching application businesses.

An MLOps Engineer, who already leads the company’s overall AI development, is scheduled to serve as the candidate’s supervisor., The company allows employees to choose between “remote work” and “in-office work” based on the nature and circumstances of their daily tasks. (Employees are expected to manage this independently.)

*For corporate department roles (accounting, PR, HR, etc.), regular in-office attendance may be requested due to certain paper-based operations.

*In-office attendance will be requested when company-wide meetings are held (expected about twice a year / transportation expenses covered).

*Approximately 90% of employees currently work remotely.

• Flextime System (Core Hours: 11:00 AM - 4:00 PM)

Standard working hours: 8 hours

Break time: 1 hour

• Overtime Work

Available

(For managerial/supervisory positions, overtime and holiday work are left to the employee’s discretion.)

• “Inspiring Experiences” Support Program

・Subsidy for expenses incurred to gain excellent experiences (Up to ¥60,000/year)

Activities, movies, dining, exhibitions, travel, seminars, schools, etc.

• Skill-Up Support Program

・Subsidy for expenses necessary to improve skills deemed essential for work (Up to ¥100,000/year)

• Dating & Marriage Hunting Support

・Subsidy for related activities (Up to ¥10,000/year)

• Babysitter Support

・Support for in-home childcare/caregiving and transportation to/from childcare facilities by a babysitter *Applicable when childcare fees exceed ¥2,200

• Lunch Support

・Subsidy provided for meals attended by two or more people (¥2,200 including tax per person) *Up to 3 times a month

• Other Social Insurance and Allowances

・Full social insurance coverage (Health Insurance, Employees’ Pension Insurance, Employment Insurance, Industrial Accident Compensation Insurance)

・Full transportation allowance (Up to ¥50,000/month) *Paid based on actual expenses

Able to deliver value to both the product and internal operations

High degree of discretion to move rapidly with a challenge-driven approach

Involved in all phases of AI utilization, from PoC to production deployment

Drive AI development while communicating closely with both the business and development teams

Direct contribution to major, life-changing milestones for users

————-( Requirements)————-

• Required (*Meet all of the following)

3+ years of product development experience using SQL and Python

Experience applying AI in B2C services

Understanding of the fundamental theories of machine learning and experience applying them in practical settings

Basic knowledge of mathematics, such as linear algebra and calculus, sufficient to understand and explain the concepts

• Preferred

Knowledge and practical experience with recommendation engines, mutual recommendations, collaborative filtering, Learning-to-Rank, re-ranking, etc.

Experience in validating effectiveness using A/B test design, causal inference, and propensity score matching

Experience in model operations using MLOps tools (SageMaker, CI/CD, etc.)

Experience using cloud infrastructure (AWS/GCP), particularly SageMaker, BigQuery, and S3

Development experience using coding agents (e.g., Codex, Claude Code)

• Ideal Applicants

Able to think and act with a user-first mindset

Proactively communicates with stakeholders and serves as a hub within the organization

Autonomously discovers and solves challenges in highly uncertain new domains, with the ability to identify and take on new initiatives

Engages not just in building products, but in the entire lifecycle-including development, operation, and improvement-with a strong focus on post-release stability and reliability